ML Engineer: LLMs & Agentic Systems for Merchant Growth

BYTEDANCE PTE. LTD.; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

ByteDance Singapore is seeking a skilled ML Engineer to design and deploy deep learning and LLM-powered tools for merchant operations and global e-commerce growth. You will harness large-scale data to create actionable insights, automate outreach, and inform pricing and campaigns.

Ideal candidates have 2+ years in ML engineering, strong Python and ML framework experience (PyTorch/TensorFlow), and a track record of turning models into business value across cross-functional teams.

Qualifications

• Candidate holds a degree in CS/AI or a related field with data mining or DL exposure.
• Strong Python programming and experience with ML frameworks and NLP tasks.
• Ability to translate algorithms into business impact with ownership.
• 2+ years as an ML Engineer, preferably in NLP or growth algorithms.

Responsibilities

• Develop and deploy deep learning and LLM-powered systems for merchant tools and growth.
• Leverage e-commerce data to power agentic systems and automated outreach optimization.
• Use ML models to predict seller performance and design campaigns and pricing.
• Collaborate cross-functionally to deliver 0-to-1 projects with measurable impact.
• Build lead-scoring, merchant tiering, and knowledge graphs to boost onboarding.
• Apply data mining and modeling to optimize pricing, promotions, and traffic.
• Communicate technical insights to both technical and non-technical stakeholders.

Skills

Python

ML Fundamentals

NLP

Deep Learning

Data Mining

Model Optimization

Communication

Teamwork

Education

Bachelor's degree in Computer Science / AI / related field

Tools

PyTorch

TensorFlow

Jupyter

Scikit-learn

Job description

ByteDance Singapore is seeking a skilled ML Engineer to design and deploy deep learning and LLM-powered tools for merchant operations and global e-commerce growth. You will harness large-scale data to create actionable insights, automate outreach, and inform pricing and campaigns.

Ideal candidates have 2+ years in ML engineering, strong Python and ML framework experience (PyTorch/TensorFlow), and a track record of turning models into business value across cross-functional teams.